allen_cahn_piratenet.yaml

defaults:
  - ppsci_default
  - TRAIN: train_default
  - TRAIN/ema: ema_default
  - TRAIN/swa: swa_default
  - EVAL: eval_default
  - INFER: infer_default
  - hydra/job/config/override_dirname/exclude_keys: exclude_keys_default
  - _self_

hydra:
  run:
    # dynamic output directory according to running time and override name
    dir: outputs_allen_cahn_piratenet/${now:%Y-%m-%d}/${now:%H-%M-%S}/${hydra.job.override_dirname}
  job:
    name: ${mode} # name of logfile
    chdir: false # keep current working directory unchanged
  callbacks:
    init_callback:
      _target_: ppsci.utils.callbacks.InitCallback
  sweep:
    # output directory for multirun
    dir: ${hydra.run.dir}
    subdir: ./

# general settings
mode: train # running mode: train/eval
seed: 42
output_dir: ${hydra:run.dir}
log_freq: 100

DATA_PATH: ./dataset/allen_cahn.mat

# model settings
MODEL:
  input_keys: [t, x]
  output_keys: [u]
  num_blocks: 3
  hidden_size: 256
  activation: tanh
  periods:
    x: [2.0, false]
  fourier:
    dim: 256
    scale: 2.0
  random_weight:
    mean: 1.0
    std: 0.1

# training settings
TRAIN:
  epochs: 300
  iters_per_epoch: 1000
  save_freq: 10
  eval_during_train: true
  eval_freq: 10
  lr_scheduler:
    epochs: ${TRAIN.epochs}
    iters_per_epoch: ${TRAIN.iters_per_epoch}
    learning_rate: 1.0e-3
    gamma: 0.9
    decay_steps: 5000
    by_epoch: false
  batch_size: 8192
  pretrained_model_path: null
  checkpoint_path: null
  causal:
    n_chunks: 32
    tol: 1.0
  grad_norm:
    update_freq: 1000
    momentum: 0.9

# evaluation settings
EVAL:
  pretrained_model_path: null
  eval_with_no_grad: true
  batch_size: 4096

# inference settings
INFER:
  pretrained_model_path: https://paddle-org.bj.bcebos.com/paddlescience/models/AllenCahn/allen_cahn_piratenet_pretrained.pdparams
  export_path: ./inference/allen_cahn
  pdmodel_path: ${INFER.export_path}.pdmodel
  pdiparams_path: ${INFER.export_path}.pdiparams
  onnx_path: ${INFER.export_path}.onnx
  device: gpu
  engine: native
  precision: fp32
  ir_optim: true
  min_subgraph_size: 5
  gpu_mem: 2000
  gpu_id: 0
  max_batch_size: 1024
  num_cpu_threads: 10
  batch_size: 1024